During normal aging, pyramidal cells in the primate dorsolateral prefrontal cortex (LPFC) undergo significant structural and functional changes associated with cognitive deficits. Pyramidal cells in the primary visual cortex (V1) are comparatively spared. The parent project of this Supplement (R01 AG059028) analyzes the selective vulnerability of neurons and associated networks in LPFC compared to V1 in aging rhesus monkeys, and the role of age-related increases in oxidative stress, inflammation, and vascular dysfunction in high-susceptibility LPFC neurons. We also propose that curcumin, an antioxidant and anti-inflammatory polyphenol, ameliorates age-related molecular, structural, and behavioral changes. We use a unique combination of state-of-the art physiological, anatomical and computational approaches, and behavioral assessment of aging monkeys, under control conditions and following therapeutic treatment with curcumin. This Supplement application (PA-18-591) represents a logical extension of this work to the human brain by assessing cellular alterations and neuronal demise in postmortem brains from Alzheimer?s disease (AD) compared to neurotypical control individuals. We focus on subsets of large pyramidal neurons severely and preferentially vulnerable in AD, identifiable by a high content of dephosphorylated neurofilament proteins and located in deep layer 3 and layer 5 in primates. Our previous analyses revealed that these neurons undergo tangle formation in early stages of AD at a faster rate than other pyramidal cells. We will use the same highly multiplexed quantitative immunofluorescence platform together with rigorous stereologic designs to analyze the molecular phenotype of these neurons in AD cases with early (Clinical Dementia Scores [CDR] 0.5) and definite (CDR 3) dementia compared to controls (CDR 0). We will characterize in detail the protein expression profiles of neocortical neuron subsets in the normally aging human brain and through AD progression by imaging on the same tissue section large numbers of biomarkers, enabling classification of cell types and states on a cell-by-cell basis. Data-driven machine-learning techniques will be applied to assign neuronal subclasses based on molecular phenotype. We will analyze areas 9/46 (LPFC), which is affected in AD, and 17 (V1), which is generally spared in AD, replicating the experimental design of the parent project. Using many molecular markers from the parent project, we will study the microenvironment of vulnerable and non-vulnerable neurons, including glial and vascular cells, and extracellular pathology, at a layer-level of resolution. We expect to uncover potential diagnostic and therapeutic targets that could ultimately provide new approaches for earlier disease detection and prevention of progressive loss of critical neurons in AD. This Supplement and its parent project will yield novel and key information on the neural substrates of cognitive decline in aging primates and provide insight into specific mechanisms of action of protective anti-inflammatory and anti-oxidants in normal and pathological brain aging.